Mining the Detector Responses of a Conducting Polymer Composite-Based Electronic Nose

Arrays of polymer films embedded with conductive or resistive material have attracted significant attention as “electronic noses”. Sorption of a vapor into the polymer films causes physical swelling, which leads to a change in the DC electrical resistance of the film. Like the receptors of the mammalian olfactory system, each polymer-based detector responds to more than one analyte and each analyte elicits a response from more than one detector. The DC resistance across the array of detectors is sampled versus time producing a multivariate time-series. Except when rapid response is critical, this multivariate time-series can be converted into a vector representation by focusing on the steady-state behavior and calculating the relative change in resistance in each channel relative to an initial baseline. In this paper, we provide an overview of our efforts to mine useful information from electronic nose data. Four case studies are presented: rapid detection of DNT (dinitrotoluene) vapors at very low concentrations (< 1 part-per-billion), pairwise discrimination between chemically similar analytes (e.g., H2O and D2O; heptane and hexane), prediction of human percepts of odor quality from electronic nose detector responses, and classification of vapors into the appropriate chemical family (e.g., saying methanol is an alcohol without having previously smelled methanol). keywords: electronic nose, scientific datasets, case study/application, pattern recognition, classification, statistical methods ∗1. JPL, M/S 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, [email protected] †2. WUSTL, Campus Box 1134, St. Louis, MO 63130, [email protected] ‡3. Caltech, M/S 127-72, Pasadena, CA 91125, [email protected] 1 Copyright © by SIAM. Unauthorized reproduction of this article is prohibited burlm re 2001/2/17 page 2 ✐ ✐